Merge pull request #40 from biolab/old_url

Blogs: Add oldUrl property

.gitignore

@@ -47,4 +47,7 @@ blogPosts.json
 search.json
 public/**/__webp-images__
 
-external
+external
+
+# pycharm
+.idea/

public/blog/2010-03-debian-repository-lives/debian-repository-lives.md

@@ -4,7 +4,7 @@ date: '2010-03-04 01:56:00+00:00'
 draft: false
 title: "Debian repository lives!"
 blog: ["debian" ,"distribution" ,"download" ,"packaging" ]
-
+oldUrl: "/blog/2010/03/04/debian-repository-lives/"
 ---
 
 We have made still-experimental-but-probably-working Debian repository with daily built Orange packages. Currently without add-ons.

public/blog/2011-02-biolab-retreat-februar-2011/biolab-retreat-februar-2011.md

@@ -4,6 +4,7 @@ date: '2011-02-11 13:41:00+00:00'
 draft: false
 title: "Biolab retreat Februar 2011"
 blog: ["bohinj" ,"orange25" ,"retreat" ]
+oldUrl: "/blog/2011/02/11/biolab-retreat-februar-2011/"
 ---
 
 From Wednesday, 2nd February 2011, to Saturday, 5th February 2011, we have been on working retreat at [Lake Bohinj](http://en.wikipedia.org/wiki/Lake_Bohinj). The whole [Bioinformatics Laboratory](http://www.biolab.si/) of the [Faculty of Computer and Information technology](http://www.fri.uni-lj.si/) has temporary moved to a nice house just few meters from the lake, enjoing the nature and without any distractions. Plan: working on the next version of Orange, [Orange 2.5](http://orange.biolab.si/trac/intertrac/wiki%3AOrange25) and documentation rewrite. Orange 2.5 will have a better and restructured Python scripting interface along with great and shinny documentation.

public/blog/2011-03-data-loading-speedups/data-loading-speedups.md

@@ -4,6 +4,7 @@ date: '2011-03-28 13:04:00+00:00'
 draft: false
 title: "Data loading speedups"
 blog: ["dataloading" ,"performance" ]
+oldUrl: "/blog/2011/03/28/data-loading-speedups/"
 ---
 
 Orange has been loading data faster since the end of February, especially if there are many attributes in the file.

public/blog/2011-03-orange-has-been-accepted-into-gsoc-2011/orange-has-been-accepted-into-gsoc-2011.md

@@ -4,6 +4,7 @@ date: "2011-03-18 21:10:00+00:00"
 draft: false
 title: "Orange has been accepted into GSoC 2011"
 blog: ["gsoc"]
+oldUrl: "/blog/2011/03/18/orange-has-been-accepted-into-gsoc-2011/"
 ---
 
 This year Orange has been accepted into the [Google summer of Code](http://socghop.appspot.com/gsoc/homepage/google/gsoc2011) program as a mentoring organization. It is one of [175 open-source organizations/projects/groups](http://socghop.appspot.com/gsoc/accepted_orgs/google/gsoc2011) which will this year mentor students while they will be working on those accepted open source projects.

public/blog/2011-03-our-gsoc-2011-posters/our-gsoc-2011-posters.md

@@ -4,6 +4,7 @@ date: '2011-03-29 10:12:00+00:00'
 draft: false
 title: "Our GSoC 2011 posters"
 blog: ["gsoc" ]
+oldUrl: "/blog/2011/03/29/our-gsoc-2011-posters/"
 ---
 
 We have made our own recruitment posters for this year's Google Summer of Code inviting students to participate.

public/blog/2011-04-accepted-gsoc-2011-students-announced/accepted-gsoc-2011-students-announced.md

@@ -4,6 +4,7 @@ date: '2011-04-25 08:22:00+00:00'
 draft: false
 title: "Accepted GSoC 2011 students announced"
 blog: ["gsoc" ]
+oldUrl: "/blog/2011/04/25/accepted-gsoc-2011-students-announced/"
 ---
 
 Accepted proposals/projects for Google Summer of Code 2011 have been [announced](http://socghop.appspot.com/gsoc/projects/list/google/gsoc2011). We got 3 students which will this year work on Orange:  

public/blog/2011-04-student-application-period-for-gsoc-2011-has-ended/student-application-period-for-gsoc-2011-has-ended.md

@@ -4,6 +4,7 @@ date: '2011-04-08 07:53:00+00:00'
 draft: false
 title: "Student application period for GSoC 2011 has ended"
 blog: ["gsoc" ]
+oldUrl: "/blog/2011/04/08/student-application-period-for-gsoc-2011-has-ended/"
 ---
 
 Student application period for [Google Summer of Code 2011](http://socghop.appspot.com/gsoc/homepage/google/gsoc2011) has ended. We got 47 proposals from students all around the world. Now it is time for us to evaluate them and select the best proposals and the best students to work this year on Orange.

public/blog/2011-05-orange-2-5-progress/orange-2-5-progress.md

@@ -4,6 +4,7 @@ date: '2011-05-20 15:08:00+00:00'
 draft: false
 title: "Orange 2.5 progress"
 blog: ["orange25" ]
+oldUrl: "/blog/2011/05/20/orange-2-5-progress/"
 ---
 
 We decided that we should reorganize Orange to provide more intuitive interface to the scripting interface. The next release, Orange 2.5 is getting better every day. But fear not, dear reader, we are working hard to ensure that your scripts will still work.

public/blog/2011-06-contact-us/contact-us.md

@@ -4,6 +4,7 @@ date: '2011-06-14 11:50:00+00:00'
 draft: false
 title: "Contact us!"
 blog: ["website" ]
+oldUrl: "/blog/2011/06/14/contact-us/"
 ---
 
 We have added a simple [contact form](/contact/) so that you can get in direct contact with us. Please do not misuse it (we will simply ignore you). Support and other general questions should be posted in our [forum](/forum/) and for issues with Orange you should use our [ticketing system](/trac/) to report them.

public/blog/2011-06-debian-packages-for-squeeze/debian-packages-for-squeeze.md

@@ -4,6 +4,7 @@ date: '2011-06-30 00:44:00+00:00'
 draft: false
 title: "Debian packages for Squeeze"
 blog: ["debian" ,"distribution" ,"download" ,"packaging" ]
+oldUrl: "/blog/2011/06/30/debian-packages-for-squeeze/"
 ---
 
 We have updated our daily Debian packages to Squeeze (current Debian stable). You just have to reconfigure our package repository in your **/etc/apt/sources.list** to:

public/blog/2011-06-orange-gsoc-mf-techniques-for-data-mining/orange-gsoc-mf-techniques-for-data-mining.md

@@ -4,6 +4,7 @@ date: '2011-06-24 22:10:00+00:00'
 draft: false
 title: "Orange GSoC: MF Techniques for Data Mining"
 blog: ["gsoc" ,"matrixfactorization" ]
+oldUrl: "/blog/2011/06/24/orange-gsoc-mf-techniques-for-data-mining/"
 ---
 
 I am one of three students who are working on GSoC projects for Orange this year. The objective of the project Matrix Factorization Techniques for Data Mining is to provide the Orange community with a unified and efficient interface to matrix factorization algorithms and methods. 

public/blog/2011-06-orange-gsoc-visualizations-with-qt/orange-gsoc-visualizations-with-qt.md

@@ -4,6 +4,7 @@ date: '2011-06-30 12:55:00+00:00'
 draft: false
 title: "Orange GSoC: Visualizations with Qt"
 blog: ["gsoc" ,"visualization" ]
+oldUrl: "/blog/2011/06/30/orange-gsoc-visualizations-with-qt/"
 ---
 
 Hello, my name is Miha Čančula and this summer I'm working on Orange as part of Google's Summer of Code program, mentored by Miha Štajdohar. My task is to replace the current visualization framework based on Qwt with a custom library, depending only on Qt. This library will better support Orange's very specific visualizations and will replace the unmaintained PyQwt. 

public/blog/2011-06-orange-t-shirts/orange-t-shirts.md

@@ -4,6 +4,7 @@ date: '2011-06-24 10:43:00+00:00'
 draft: false
 title: "Orange T-shirts"
 blog: ["orange3" ]
+oldUrl: "/blog/2011/06/24/orange-t-shirts/"
 ---
 
 If you maybe missed on [our Facebook page](https://www.facebook.com/orangedm): we have made our own fruity t-shirts. They are simply awesome and show to everybody around you that you have a taste! Just check the handsomeness:

public/blog/2011-07-fink-packages-now-also-64-bit/fink-packages-now-also-64-bit.md

@@ -4,6 +4,7 @@ date: '2011-07-03 12:31:00+00:00'
 draft: false
 title: "Fink packages now also 64-bit"
 blog: ["distribution" ,"download" ,"packaging" ]
+oldUrl: "/blog/2011/07/03/fink-packages-now-also-64-bit/"
 ---
 
 [Fink packages](http://www.finkproject.org/) (we are using for system-wide Orange installations on Mac OS X) were updated to 64-bit. So if you were using 64-bit Fink installation you will be now able also to use Orange (and our binary Fink repository of already compiled packages). Just use this [this installation script](/svn/orange/trunk/install-scripts/mac/fink-selfupdate-orange.sh) to configure your local Fink installation to use our binary Fink repository and add information about Orange packages (they are not available among official Fink packages).

public/blog/2011-07-networkx-in-orange/networkx-in-orange.md

@@ -4,6 +4,7 @@ date: '2011-07-29 18:56:00+00:00'
 draft: false
 title: "NetworkX in Orange"
 blog: ["analysis" ,"network" ,"networkx" ,"visualization" ]
+oldUrl: "/blog/2011/07/29/networkx-in-orange/"
 ---
 
 [NetworkX](http://networkx.lanl.gov/) – a popular open-source python library for network analysis has finally found its way into Orange. It is now used as a base class for network representation in all Orange modules and widgets. By that, we offered to the widespread network community a fruitful and fun way to visualize and explore networks, using their existing NetworkX scripts. It has never been easier to combine network analysis and visualization with existing machine learning and data discovery methods.

public/blog/2011-07-orange-gsoc-multi-label-classification-implementation/orange-gsoc-multi-label-classification-implementation.md

@@ -4,6 +4,7 @@ date: '2011-07-20 11:35:00+00:00'
 draft: false
 title: "Orange GSoC: Multi-label Classification Implementation"
 blog: ["gsoc" ,"multilabel" ]
+oldUrl: "/blog/2011/07/20/orange-gsoc-multi-label-classification-implementation/"
 ---
 
 Multi-label classification is one of the three projects of Google Summer Code 2011 for Orange. The main goal is to extend the Orange to support multi-label, including dataset support, two basic multi-label classifications-problem-transformation methods & algorithm adaptation methods, evaluation measures, GUI support, documentation, testing, and so on.

public/blog/2011-08-faster-classification-and-regression-trees/faster-classification-and-regression-trees.md

@@ -4,6 +4,7 @@ date: '2011-08-24 22:26:00+00:00'
 draft: false
 title: "Faster classification and regression trees"
 blog: ["classification" ,"regression" ,"tree" ]
+oldUrl: "/blog/2011/08/24/faster-classification-and-regression-trees/"
 ---
 
 **SimpleTreeLearner** is an implementation of classification and regression trees that sacrifices flexibility for speed. A benchmark on 42 different datasets reveals that **SimpleTreeLearner** is **11 times faster** than the original **TreeLearner**.

public/blog/2011-08-golden-sublime-triangles-in-orange/golden-sublime-triangles-in-orange.md

@@ -4,6 +4,7 @@ date: '2011-08-19 14:18:00+00:00'
 draft: false
 title: "Golden (sublime) triangles in Orange"
 blog: ["visualization" ]
+oldUrl: "/blog/2011/08/19/golden-sublime-triangles-in-orange/"
 ---
 
 Hand in hand with the development of the [new visualization framework](/blog/2011/06/30/orange-gsoc-visualizations-with-qt/) and the financial crisis we are putting some gold into Orange. The arrows at the ends of the axes are, as of today, small [golden triangles](http://en.wikipedia.org/wiki/Golden_triangle_(mathematics)). See the changes in [owaxis.py](http://orange.biolab.si/trac/intertrac/source%3Atrunk/orange/OrangeWidgets/plot/owaxis.py)!

public/blog/2011-08-orange-at-ismbeccb-2011/orange-at-ismbeccb-2011.md

@@ -4,6 +4,7 @@ date: '2011-08-03 09:14:00+00:00'
 draft: false
 title: "Orange at ISMB/ECCB 2011"
 blog: ["bioinformatics" ,"bioorange" ,"conference" ]
+oldUrl: "/blog/2011/08/03/orange-at-ismbeccb-2011/"
 ---
 
 We presented the [Orange Bioinformatics add-on](/bio/) at the [ISMB/ECCB](http://www.iscb.org/ismbeccb2011/) conference in Vienna, a joined event covering both 19th Annual International Conference on Intelligent Systems for Molecular Biology and 10th European Conference on Computational Biology.

public/blog/2011-09-3d-visualizations-in-orange/3d-visualizations-in-orange.md

@@ -4,6 +4,7 @@ date: '2011-09-07 10:30:00+00:00'
 draft: false
 title: "3D Visualizations in Orange"
 blog: ["opengl" ,"visualization" ]
+oldUrl: "/blog/2011/09/07/3d-visualizations-in-orange/"
 ---
 
 Over the summer I worked (and still do) on several new 3D visualization widgets as well as a 3D plotting library they use, which will hopefully simplify making more widgets. The library is designed to be similar in terms of API to the new [Qt plotting library](/blog/2011/09/03/gsoc-review-visualizations-with-qt/) Noughmad is working on.

public/blog/2011-09-debian-packages-support-multiple-python-versions-now/debian-packages-support-multiple-python-versions-now.md

@@ -4,6 +4,7 @@ date: '2011-09-13 00:32:00+00:00'
 draft: false
 title: "Debian packages support multiple Python versions now"
 blog: ["debian" ,"packaging" ,"python" ]
+oldUrl: "/blog/2011/09/13/debian-packages-support-multiple-python-versions-now/"
 ---
 
 We have created Debian packages for multiple Python versions. This means that they work now with both Python 2.6 and 2.7 out of the box, or if you compile them manually, with any (supported) version you have installed on your (Debian-based) system.

public/blog/2011-09-gsoc-review-mf-matrix-factorization-techniques-for-data-mining/gsoc-review-mf-matrix-factorization-techniques-for-data-mining.md

@@ -4,6 +4,7 @@ date: '2011-09-01 23:48:00+00:00'
 draft: false
 title: "GSoC Review: MF - Matrix Factorization Techniques for Data Mining"
 blog: ["gsoc" ,"matrixfactorization" ]
+oldUrl: "/blog/2011/09/01/gsoc-review-mf-matrix-factorization-techniques-for-data-mining/"
 ---
 
 MF - Matrix Factorization Techniques for Data Mining is a Python scripting library which includes a number of published matrix factorization algorithms, initialization methods, quality and performance measures and facilitates the combination of these to produce new strategies. The library represents a unified and efficient interface to matrix factorization algorithms and methods.

public/blog/2011-09-gsoc-review-multi-label-classification-implementation/gsoc-review-multi-label-classification-implementation.md

@@ -4,6 +4,7 @@ date: '2011-09-02 05:47:00+00:00'
 draft: false
 title: "GSoC Review: Multi-label Classification Implementation"
 blog: ["classification" ,"gsoc" ,"multilabel" ]
+oldUrl: "/blog/2011/09/02/gsoc-review-multi-label-classification-implementation/"
 ---
 
 Traditional single-label classification is concerned with learning from a set of examples that are associated with a single label **l** from a set of disjoint labels **L**, **|L|** > **1**. If **|L|** = **2**, then the learning problem is called a binary classification problem, while if **|L|** > **2**, then it is called a multi-class classification problem (Tsoumakas & Katakis, 2007).

public/blog/2011-09-gsoc-review-visualizations-with-qt/gsoc-review-visualizations-with-qt.md

@@ -4,6 +4,7 @@ date: '2011-09-03 08:28:00+00:00'
 draft: false
 title: "GSoC Review: Visualizations with Qt"
 blog: ["gsoc" ,"plot" ,"qt" ,"visualization" ]
+oldUrl: "/blog/2011/09/03/gsoc-review-visualizations-with-qt/"
 ---
 
 During the course of this summer, I created a new plotting library for Orange plot, replacing the use of PyQwt. I can say that I have succesfully completed my project, but the library (and especially the visualization widgets) could still use some more work. The new library supports a similar interface, so little change is needed to convert individual widgets, but it also has several advantages over the old implementation:  

public/blog/2011-09-orange-badges-are-here/orange-badges-are-here.md

@@ -4,6 +4,7 @@ date: '2011-09-04 03:29:00+00:00'
 draft: false
 title: "Orange badges are here!"
 blog: ["orange3" ]
+oldUrl: "/blog/2011/09/04/orange-badges-are-here/"
 ---
 
 Orange badges are here! They come in two flavors. Tasty!

public/blog/2011-10-gsoc-mentor-summit/gsoc-mentor-summit.md

@@ -4,6 +4,7 @@ date: '2011-10-26 11:29:00+00:00'
 draft: false
 title: "GSoC Mentor Summit"
 blog: ["gsoc" ]
+oldUrl: "/blog/2011/10/26/gsoc-mentor-summit/"
 ---
 
 On 22th and 23th October 2011 there was [Google Summer of Code](https://code.google.com/soc/) [Mentor Summit](http://gsoc-wiki.osuosl.org/index.php/2011) in [Mountain View, California](http://en.wikipedia.org/wiki/Mountain_View,_California). Google Summer of Code is Google's program for encouraging students to work on open-source projects during their summer break. Because this year Orange participated in this program too, we decided to participate also in this summit and get to know other mentors, other open-source projects and organizations, exchange our experiences, learn something new, and improve our connections and collaborations with others.

public/blog/2011-12-earth-multivariate-adaptive-regression-splines/earth-multivariate-adaptive-regression-splines.md

@@ -4,6 +4,7 @@ date: '2011-12-20 12:22:00+00:00'
 draft: false
 title: "Earth - Multivariate adaptive regression splines"
 blog: ["regression" ]
+oldUrl: "/blog/2011/12/20/earth-multivariate-adaptive-regression-splines/"
 ---
 
 There have recently been some additions to the lineup of Orange learners. One of these is Orange.regression.earth.EarthLearner. It is an Orange interface to the [Earth](http://www.milbo.users.sonic.net/earth/) library written by Stephen Milborrow implementing [Multivariate adaptive regression splines](http://en.wikipedia.org/wiki/Multivariate_adaptive_regression_splines).

public/blog/2011-12-orange-2-5-code-conversion/orange-2-5-code-conversion.md

@@ -4,6 +4,7 @@ date: '2011-12-20 12:21:00+00:00'
 draft: false
 title: "Orange 2.5: code conversion"
 blog: ["orange25" ]
+oldUrl: "/blog/2011/12/20/orange-2-5-code-conversion/"
 ---
 
 Orange 2.5 unifies Orange's C++ core and Python modules into a single module hierarchy. To use the new module hierarchy, import **Orange** instead of **orange** and accompanying **orng*** modules. While we will maintain backward compatibility in 2.* releases, we nevertheless suggest programmers to use the new interface. The provided [conversion tool](http://orange.biolab.si/trac/intertrac/wiki%3AOrange25/RefactoringTool) can help refactor your code to use the new interface.

public/blog/2011-12-random-forest-switches-to-simple-tree-learner-by-default/random-forest-switches-to-simple-tree-learner-by-default.md

@@ -4,6 +4,7 @@ date: '2011-12-08 15:28:00+00:00'
 draft: false
 title: "Random forest switches to Simple tree learner by default"
 blog: ["forestlearner" ,"simpletreelearner" ]
+oldUrl: "/blog/2011/12/08/random-forest-switches-to-simple-tree-learner-by-default/"
 ---
 
 Random forest classifiers now use **Orange.classification.tree.SimpleTreeLearner**by default, which considerably shortens their construction times.

public/blog/2012-01-multi-label-classification-and-multi-target-prediction-in-orange/multi-label-classification-and-multi-target-prediction-in-orange.md

@@ -4,6 +4,7 @@ date: '2012-01-09 12:41:00+00:00'
 draft: false
 title: "Multi-label classification (and Multi-target prediction) in Orange"
 blog: ["classification" ,"gsoc" ,"mlc" ,"multilabel" ]
+oldUrl: "/blog/2012/01/09/multi-label-classification-and-multi-target-prediction-in-orange/"
 ---
 
 The last summer, student Wencan Luo participated in [Google Summer of Code](https://code.google.com/soc/) to implement [Multi-label Classification in Orange](/blog/2011/09/02/gsoc-review-multi-label-classification-implementation/). He provided a framework, implemented a few algorithms and some prototype widgets. His work has been "hidden" in our repositories for too long; finally, we have merged part of his code into Orange (widgets are not there yet ...) and added a more general support for multi-target prediction.

public/blog/2012-01-new-orange-icons/new-orange-icons.md

@@ -4,6 +4,7 @@ date: '2012-01-06 14:54:00+00:00'
 draft: false
 title: "New Orange icons"
 blog: ["icons" ]
+oldUrl: "/blog/2012/01/06/new-orange-icons/"
 ---
 
 As new and new widgets with new features are added to Orange, icons for them have to be drawn. Most of the time those are just some quick sketches or even missing altogether. But now we are starting to redraw and unify them. A few of them have already been made.

public/blog/2012-01-orange-2-5a2-available/orange-2-5a2-available.md

@@ -4,6 +4,7 @@ date: '2012-01-23 11:23:00+00:00'
 draft: false
 title: "Orange 2.5a2 available"
 blog: ["gsoc" ,"pypi" ,"release" ]
+oldUrl: "/blog/2012/01/23/orange-2-5a2-available/"
 ---
 
 Orange 2.5a2 has been uploaded to [PyPI](http://pypi.python.org/pypi/Orange). It now includes basic support for multi-label classification (developed during the Google Summer of Code 2011), some new widget icons and documentation for basket format. Release is also tagged on our [Bitbucket repository](https://bitbucket.org/biolab/orange/).

public/blog/2012-01-parallel-orange/parallel-orange.md

@@ -4,6 +4,7 @@ date: '2012-01-03 08:59:00+00:00'
 draft: false
 title: "Parallel Orange?"
 blog: ["parallelization" ]
+oldUrl: "/blog/2012/01/03/parallel-orange/"
 ---
 
 We attended a [NIPS 2011](http://nips.cc/) workshop on [processing and learning from large scale data](http://biglearn.org/). Various presenters showed different tools and frameworks that can be used when developing algorithms suitable for dealing with large scale data, but none of them were written in Python and as such, not useful for Orange. We have been looking for a framework that would help us run code in parallel for some time, but so far with no luck.

public/blog/2012-02-new-in-orange-partial-least-squares-regression/new-in-orange-partial-least-squares-regression.md

@@ -4,6 +4,7 @@ date: '2012-02-02 16:21:00+00:00'
 draft: false
 title: "New in Orange: Partial least squares regression"
 blog: ["multitarget" ,"pls" ,"regression" ]
+oldUrl: "/blog/2012/02/02/new-in-orange-partial-least-squares-regression/"
 ---
 
 [Partial least squares regression](http://en.wikipedia.org/wiki/Partial_least_squares_regression) is a regression technique which supports multiple response variables. PLS regression is very popular in areas such as bioinformatics, chemometrics etc. where the number of observations is usually less than the number of measured variables and where there exists multicollinearity among the predictor variables. In such situations, standard regression techniques would usually fail. The PLS regression is now available in Orange (see [documentation](/doc/reference/Orange.regression.pls))!

public/blog/2012-02-random-decisions-behind-your-back/random-decisions-behind-your-back.md

@@ -4,6 +4,7 @@ date: '2012-02-05 20:30:00+00:00'
 draft: false
 title: "Random decisions behind your back"
 blog: ["tree" ]
+oldUrl: "/blog/2012/02/05/random-decisions-behind-your-back/"
 ---
 
 When Orange builds a decision tree, candidate attributes are evaluated and the best candidate is chosen. But what if two or more share the first place? Most machine learning systems don't care about it and always take the first, which is unfair and, besides, has strange effects: the induced model and, consequentially, its accuracy depends upon the order of attributes. Which shouldn't be.